Template-Directed Ligation of Tethered Mononucleotides by T4 DNA Ligase for Kinase Ribozyme Selection

Background: In vitro selection of kinase ribozymes for small molecule metabolites, such as free nucleosides, will require partition systems that discriminate active from inactive RNA species. While nucleic acid catalysis of phosphoryl transfer is well established for phosphorylation of 59 or 29 OH of oligonucleotide substrates, phosphorylation of diffusible small molecules has not been demonstrated. Methodology/Principal Findings: This study demonstrates the ability of T4 DNA ligase to capture RNA strands in which a tethered monodeoxynucleoside has acquired a 59 phosphate. The ligation reaction therefore mimics the partition step of a selection for nucleoside kinase (deoxy)ribozymes. Ligation with tethered substrates was considerably slower than with nicked, fully duplex DNA, even though the deoxynucleotides at the ligation junction were Watson-Crick base paired in the tethered substrate. Ligation increased markedly when the bridging template strand contained unpaired spacer nucleotides across from the flexible tether, according to the trends: A2.A1.A3.A4.A0.A6.A8.A10 and T2.T3.T4.T6<T1.T8.T10. Bridging T’s generally gave higher yield of ligated product than bridging A’s. ATP concentrations above 33 mM accumulated adenylated intermediate and decreased yields of the gap-sealed product, likely due to re-adenylation of dissociated enzyme. Under optimized conditions, T4 DNA ligase efficiently (.90%) joined a correctly paired, or T:G wobble-paired, substrate on the 39 side of the ligation junction while discriminating approximately 100-fold against most mispaire

Multimodal Medical Volume Registration Based on Spherical Markers

We propose volume registration procedures based on spherical artificial markers presented in medical multimodal data sets (MRI and CT, especially). The procedures proposed are either semi-automatic or fully-automatic. A semi-automatic approach requires to label approximate locations of the spherical markers in the data sets and then registration operates autonomically. A fully-automatic approach does not require any user interaction, i.e. all registration subtasks – namely segmentation of spheres, finding the correspondence between two sets of spheres and, finally, computing geometrical transformation that maps the first set of spheres onto the second one – are performed automatically by the computer

Texture-based Automated Quantification of Interstitial Lung Disease: Correlation With the Visual Score

Purpose of the Study: The quantification of various disease patterns in the lung parenchyma remains a challenge. In this study the texture analysis algorithm 3D-AMFM (Adaptive Multiple Feature Method) contained in the software PASS (University of Iowa) was applied with interstitial lung disease (ILD). We checked for the statistical accuracy and reliabity of the method by standard tests compared to visual scoring. Methods: Based on a Bayesian classifier, a training data base including texture patterns (normal, ground glass, honey combing, emphysema) from 1300 volumes of interest (VOIs; 151515 pixels) of 47 selected patients with mixed ILDs was built up. Another 18 patients with a typical thin-section CT pattern of usual interstitial pneumonia (UIP) (n=9) and nonspecific interstitial pneumonia (NSIP) (n=9) were independently analyzed and visually quantified at 5 pre-established levels by two experienced chest radiologists. The same thin-section CT scans were analyzed with 3D-AMFM. Wilcoxon test was used to evaluate the correlation between the visual scores and the computed results. Results: The mean extent of honeycombing, ground glass and emphysema was 5.4%, 43.5% and 2.1% by the visual score and 19.4%, 44.3% and 0.6% by the 3D-AMFM, respectively. There was close correlation between visual score and 3D-AMFM for both the extent of ground glass (P=0.546) and emphysema (P=0.099), but worse for the extent of honey combing (P=0.000837). Conclusions: The 3D-AMFM system is a promising and effective tool for ILD quantification, showing clinical acceptable correlation with human observer. The overestimation of honeycombing by 3D-AMFM is probably caused by small vessels and airways. The continuing development of the feature data base and the inclusion of further pathologic texture patterns will improve quantification of disease and provide objective measures of disease progression